Top Flume Interview Questions and Answers
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Today we will discuss in this article, “Top Flume Interview Questions and answers” we are providing Advanced Apache Flume Interview Questions that will help you in cracking your interview as well as to acquire dream career as Apache Flume Developer. If we talk about the current world, there are a lot of opportunities in Flume Development in many reputed companies across the world. On the basis of research, we can say Flume has a market share of about 70.37%. Hence, we have huge opportunity to move ahead in our career in Apache Flume Development. However, to go for Flume jobs it is important to learn Apache Flume in deep. So, if you’re looking for Flume Interview Questions & Answers for Experienced or Freshers, you are at right place.
2. What is Apache Flume
As we know, while it comes to efficiently and reliably collect, aggregate and transfer massive amounts of data from one or more sources to a centralized data source we use Apache Flume. However, it can ingest any kind of data including log data, event data, network data, social-media generated data, email messages, message queues etc since data sources are customizable in Flume. Now, after this introduction, let’s begin the learning by following Flume Interview Questions.
However, there are many more insights of Apache Flume, to learn all follow the link: Apache Flume Tutorial – Flume Introduction, Features & Architecture
3. Flume Interview Questions and Answers
There is a list of some prominent Flume Interview Questions. Let’s discuss all possible Flume Interview Questions:
Q 1. What is Flume?
Answer: A distributed service for collecting, aggregating, and moving large amounts of log data, is Flume.
Q 2. Explain the core components of Flume.
Answer: There are various core components of Flume available. They are –
- Event- Event is the single log entry or unit of data which we transport further.
- Source- Source is the component by which data enters Flume workflows.
- Sink- For transporting data to the desired destination sink is responsible.
- Channel-Channel is nothing but a duct between the Sink and Source.
- Agent- Agent is what we have known as any JVM that runs Flume.
- Client- Client transmits the event to the source that operates with the agent.
Learn each component in detail, follow the link: Flume Architecture.
Q 3. Which is the reliable channel in Flume to ensure that there is no data loss?
Answer: Among the 3 channels JDBC, FILE and MEMORY, FILE Channel is the most reliable channel.
Q 4. How can Flume be used with HBase?
Answer: There are two types of HBase sinks. So, we can use Flume with HBase using one of the two HBase sinks –
- HBaseSink (org.apache.flume.sink.hbase.HBaseSink)
supports secure HBase clusters and also the novel HBase IPC that was introduced in the version HBase 0.96.
- AsyncHBaseSink (org.apache.flume.sink.hbase.AsyncHBaseSink)
It can easily make non-blocking calls to HBase, it means it has better performance than HBase sink.
Q 5. What is an Agent?
Answer: In Apache Flume, an independent daemon process (JVM) is what we call an agent. At first, it receives events from clients or other agents. Afterwards, it forwards it to its next destination that is sink or agent. Note that, it is possible that Flume can have more than one agent. Also, refer the below image to understand the Flume Agent.
To know what is Flume Agent, you must refer Architectures of Flume
Q 6. Is it possible to leverage real-time analysis of the big data collected by Flume directly? If yes, then explain how?
Answer: By using MorphlineSolrSink we can extract, transform and load Data from Flume in real-time into Apache Solr servers.
Q 7. What is a channel?
Answer: A transient store that receives the events from the source also buffers them till they are consumed by sinks is what we call a Flume channel. To be very specific it acts as a bridge between the sources and the sinks in Flume.
Basically, these channels can work with any number of sources and sinks are they are fully transactional.
Like − JDBC channel, File system channel, Memory channel, etc.
However, learn Flume Channels in detail, follow the link: Apache Flume Channel and its types
Q 8. Explain about the different channel types in Flume. Which channel type is faster?
Answer: There are 3 types of different built-in channel in Flume. they are-
- MEMORY Channel – Through this MEMORY Channel Events are read from the source into memory and passed to the sink.
- JDBC Channel – It stores the events in an embedded Derby database.
- FILE Channel –It writes the contents to a file on the file system after reading the event from a source. The file is deleted only after the contents are successfully delivered to the sink.
While we come to the fastest channel, it is the MEMORY Channel. It is the fastest channel among the three. Although, make sure it has the risk of data loss.
Q 9. What is Interceptor?
Answer: To alter/inspect flume events which are transferred between source and channel, we use Flume Interceptors.
However, learn Flume Interceptors in detail, follow the link: Apache Flume Interceptors and Its Types
Q 10. Explain about the replication and multiplexing selectors in Flume.
Answer: Basically, to handle multiple channels, we use Channel selectors. Moreover, an event can be written just to a single channel or to multiple channels, on the basis of Flume header value. By default, it is the Replicating selector, if a channel selector is not specified to the source. Although, the same event is written to all the channels in the source’s channels list, by using the replicating selector. However, when the application has to send different events to different channels, we use Multiplexing channel selector.
Flume Interview Questions for Freshers- Q. 1,2,3,5,6,7,8,9
Flume Interview Questions for Experience- Q. 4,10
Q 11. Does Apache Flume provide support for third-party plug-ins?
Answer: Apache Flume has plug-in based architecture. Basically, it can load data from external sources and transfer it to external destinations most of the data analysts use it.
Q 12. Apache Flume support third-party plugins also?
Answer: Yes, it has 100% plugin-based architecture. Basically, it can load and ships data from external sources to an external destination which separately from Flume. HeFileRollSinknce, for streaming data most of the BigData analyst use this tool.
Q 13. Differentiate between FileSink and FileRollSink
Answer: Basically, HDFS File Sink writes the events into the Hadoop Distributed File System – HDFS while File Roll Sink stores the events into the local file system.
Q 14. Which is the Reliable Channel in Flume to ensure that there is no data loss?
Answer: FILE Channel is the most reliable channel.
Q 15. Can Flume can distribute data to multiple destinations?
Answer: Flume generally supports multiplexing flow. Here, event flows from one source to multiple channel and multiple destinations. Basically, it is achieved by defining a flow multiplexer.
Q 16. How can multi-hop agent be set up in Flume?
Answer: To setup Multi-hop agent in Apache Flume we use Avro RPC Bridge mechanism.
Q 17. Why are we using Flume?
Answer: Basically, to get log data from social media sites most often Hadoop developer use this too. However, for aggregating and moving the very large amount of data it is developed by Cloudera. Majorly, we use it to gather log files from different sources and asynchronously persist in the Hadoop cluster.
learn in detail, follow the link: Why Flume
Q 18. What is FlumeNG?
Answer: FlumeNG is nothing but a real-time loader for streaming your data into Hadoop. Basically, it stores data in HDFS and HBase. Thus, if we want to get started with FlumeNG, it improves on the original flume.
Q 19. Can flume provide 100% reliability to the data flow?
Answer: Flume generally offers the end-to-end reliability of the flow. Also, it uses a transactional approach to the data flow, by default.
In addition, Source and sink encapsulate in a transactional repository provides the channels. Moreover, to pass reliably from end to end flow these channels are responsible. Hence, it offers 100% reliability to the data flow.
Q 20. What is sink processors?
Answer: We generally sink processors to invoke a particular sink from the selected group of sinks. Moreover, also to create failover paths for our sinks or load balance events across multiple sinks from a channel we use sink processors.
To learn about Sink processors in detail, follow the link: Flume – Sink Processors
Flume Interview Questions for Freshers- Q. 12,13,14,15,16,17,20
Flume Interview Questions for Experience- Q. 18,19
Q 21. Explain what are the tools used in Big Data?
Answer: There are several tools available in Big Data. It includes:
Q 22. Agent communicate with other Agents?
Answer: Here, each agent runs independently. As a result, there is no single point of failure.
Q 23. Does Apache Flume provide support for third-party plug-ins?
Answer: Yes it offers support for third-party plug-ins.
Q 24. What are the complicated steps in Flume configurations?
Answer: we can process streaming data, by using Flume. Hence, if started once, there is no stop/end of the process. asynchronously it can flows data from source to HDFS via the agent. First of all, the agent should know individual components how they are connected to load data. Thus, to load streaming data configuration is the trigger. for example, consumerkey, consumersecret accessToken, and accessTokenSecret are key factors to download data from Twitter.
Q 25. Which is the reliable channel in Flume to ensure that there is no data loss?
Answer: The most reliable channel is FILE Channel among the 3 channels JDBC, FILE, and MEMORY.
Q 26. What are Flume core components?
Answer: Source, Channels, and sink are core components in Apache Flume.
Learn each component in detail, follow the link: Flume Architecture.
Q 27. What are the Data extraction tools in Hadoop?
Answer: Sqoop can be used to transfer data between RDBMS and HDFS. Flume can be used to extract the streaming data from social media, weblog etc and store it on HDFS.
Q 28. What are the important steps in the configuration?
Answer: Configuration file is the heart of the Apache Flume’s agents.
- Every Source must have at least one channel.
- Moreover, every Sink must have only one channel
- Every component must have a specific type.
Q 29. Is there any difference between FileSink and FileRollSink?
Answer: yes, there is a major difference between HDFS FileSink and FileRollSink. That HDFS File Sink writes the events into the Hadoop Distributed File System (HDFS) while File Roll Sink stores the events into the local file system.
Q 30. What is Apache Spark?
Answer: Apache Spark is a general-purpose & lightning fast cluster computing system. It provides high-level API. For example, Java, Scala, Python and R. Apache Spark is a tool for Running Spark Applications. Spark is 100 times faster than Big Data Hadoop and 10 times faster than accessing data from disk.
Flume Interview Questions for Freshers- Q. 21,22,23,25,26,27,28,30
Flume Interview Questions for Experience- Q. 24,29
Q 31. Explain data flow in Flume?
Ans. Basically, we use a framework Flume to transfer log data into HDFS. However, we can say events and log data are generated by the log servers. Also, these servers have Flume agents running on them. Moreover, these agents receive the data from the data generators.
To be more specific, in Flume there is an intermediate node which collects the data in these agents, that nodes are what we call as Collector. As same as agents, in Flume, there can be multiple collectors.
Afterwards, from all these collectors the data will be aggregated and pushed to a centralized store. Such as HBase or HDFS. To understand better, refer the following Flume Data Flow diagram, it explains Flume Data Flow model.
Learn DataFlow in detail, follow the link: Flume – Data Flow
Q 32. Types of Data Flow in Flume?
- Multi-hop Flow
Learn Hadoop from Industry Experts
Basically, before reaching the final destination there can be multiple agents and an event may travel through more than one agent, within Flume. This is what we call as multi-hop Data flow in Flume.
- Fan-out Flow
In very simple language when data transfers or the data flow from one source to multiple channels that is what we call fan-out flow. Basically, in Flume Data flow, it is of two categories −
It is the data flow where the data will be replicated in all the configured channels.
On defining Multiplexing we can say the data flow where the data will be sent to a selected channel which is mentioned in the header of the event.
- Fan-in Flow
While it comes to fan-in flow it is known as the data flow in which the data will be transferred from many sources to one channel.
Q 33. What is flume agent?
Answer: However, in Apache Flume, an independent daemon process (JVM) is what we call a Flume Agent. At first, it receives events from clients or other agents. Afterwards, it forwards it to its next destination that is sink or agent. Note that, it is possible that Flume can have more than one agent.
Q 34. What is Flume event?
Answer: The basic unit of the data which is transported inside Flume is what we call a Flume Events. Generally, it contains a payload of the byte array. Basically, we can transport it from the source to the destination accompanied by optional headers.
Q 35. Why Flume?
Answer: Apart from collecting logs from distributed systems, it is also capable of performing other use cases. like
- It Collects readings from array of sensors
- Also, it collects impressions from custom apps for an ad network
- Moreover, it collects it readings from network devices in order to monitor their performance.
- Also, preserves the reliability, scalability, manageability, and extensibility while it serves maximum number of clients with higher QoS
learn in detail, follow the link: Why Flume
Q 36. can you explain about configuration files?
Answer: Basically, in the local configuration file, the agent configuration stores. Moreover, it comprises of each agents source, sinks, and channel information.
In addition, each core components such as source, sink, and channel have properties such as name, type, and set properties.
Q 37. Tell any two feature Flume?
Answer: Any two features of Flume:
- Data Flow
In Hadoop environments, Flume works with streaming data sources. Especially which generates continuously. Such as log files.
Generally, Flume looks at the payload such as stream data or event. Also, construct a routing which is apt.
There are many more features of Apache Flume. To learn all, Follow the link: Apache Flume Features
Q 38. Any two Limitations of Flume?
Answer: Any two limitations of Flume:
- Weak Ordering Guarantee
While it comes to ordering guarantee, Apache flume is very weak in it.
In many scenarios, Flume does not guarantee that message reaching is unique. However, it is a possibility that duplicate messages might pop in at times.
There are many more Limitations of Apache Flume. To learn all, Follow the link: Limitations of Apache Flume
Q 39. What are the similarities and differences between Apache Flume and Apache Kafka?
Answer: While it comes to Flume it pushes messages to their destination via its Sinks. However, With Kafka, you need to consume messages from Kafka Broker using a Kafka Consumer API.
Q 40. Explain Reliability and Failure Handling in Apache Flume?
Answer: To guarantee reliable message delivery Flume NG, it uses channel-based transactions. Moreover, while a message moves from one agent to another, two transactions are started, one on the agent that delivers the event and the other to the agent that receives the event. However, it must receive success indication from the receiving agent in order for the sending agent to commit its transaction.
Basically, the receiving agent only returns a success indication if its own transaction commits properly first. This ensures guaranteed delivery semantics between the hops that the flow makes.
Flume Interview Questions for Freshers- Q. 31,32,33,34,35,37,38
Flume Interview Questions for Experience- Q. 36,39,40
Q 41. What is Flume Client?
Ans. Those which generates events and then sent it to one or more agents is what we call Flume Client.
Q 42. What are Channel Selectors?
Ans. To determine which channel we should select to transfer the data in case of multiple channels, we use Channel Selector.
Learn it in detail, follow the link: Channel Selectors
Q 43. What are possible types of Channel Selectors?
Ans. Channel Selectors are generally of two types −
- Default channel selectors − Replicating channel selectors which replicate all the events in each channel is what we call Default channel selectors.
- Multiplexing channel selectors − The Channel selectors which decide the channel to send an event based on the address in the header of that event are Multiplexing channel selectors.
Q 44. Can you define what is Event Serializer in Flume?
Answer: While it comes to convert a Flume event into another format for output, we use Apache Flume event serializer mechanism.
Learn it in detail: Flume – Event Serializers
Q 45. What is Streaming / Log Data?
Answer: While it comes to Streaming / Log Data, it is the data produced by various data sources and usually require to be analyzed. Data Sources like, applications servers, social networking sites, cloud servers and enterprise servers. So, that data is generally in the form of log files or events.
Q 46. What are Tools available to send the streaming data to HDFS?
Answer: There are several Tools available to send the streaming data to HDFS. They are:
- Facebook’s Scribe
- Apache Kafka
- Apache Flume
Q 47. How to Use HDFS put Command for Data Transfer from Flume to HDFS?
Answer: Basically, in handling the log data, the main challenge is to move the logs produced by multiple servers to Hadoop environment.
In order to insert data into Hadoop and read from it, Hadoop File System Shell offers commands. So, by using put command we can insert the data:
$ Hadoop fs –put /path of the required file /path in HDFS where to save the file
Learn completely about Data Transfer from Flume to HDFS, follow the link: Flume – Data Transfer to HDFS
Q 48. What are use cases of Apache Flume?
Answer: There are several use cases:
- While we want to acquire data from a variety of source and store into Hadoop system, we use Apache Flume.
- Whenever we need to handle high-velocity and high-volume data into Hadoop system, we go for Apache Flume.
- It also helps in Reliable delivery of data to the destination.
- When the velocity and volume of data increases, Flume turned as a scalable solution that can run quite easily just by adding more machine to it.
- Without incurring any downtime Flume dynamically configures the various components of the architecture.
There are many more possible use cases of Apache Flume, follow the link: Apache Flume Use Cases – Future Scope
Flume Interview Questions for Freshers- Q. 41,42,43,44,45,46
Flume Interview Questions for Experience- Q. 47
4. Conclusion: Flume Interview Questions
As a result, here we have studied the detailed list of latest Flume Interview Questions and the best possible answers to these Flume Interview Questions. Thus, we really hope these Flume Interview Questions will help you to understand the nature of Flume Interview Questions you may face during the interview. Although, if you want to ask any query regarding Flume Interview Questions, feel free to ask in the comment section.